Machine Learning Engineer

  • Full-time
  • Department: Product & Engineering

Company Description

Have you ever worked for a company that actually wanted you to bring your whole self to work every single day?

About Tradeshift
Tradeshift is a unicorn in the fintech industry. We are disrupting a typically stagnant environment by connecting companies of all sizes and providing them with the platform and network needed to create value from old processes like procurement, invoicing, payments, and workflow. We recognize that business is both messy and social - two revelations that have driven the development of Tradeshift, a platform for all your business interactions.

Team 
Tradeshift’s Machine Learning team is looking for a software engineer with machine learning experience to join our team. You will become a member of a small, highly skilled team that works on bringing machine learning to various Tradeshift products. Applications for Machine Learning will range from scanned document recognition over classification of business documents to systems that support business process automation and decision making. We believe in team-based ownership and cover the entire lifecycle from product inception, development of predictive models, integrating with other services and production support. 
We have great autonomy and responsibility to choose the best solutions, technologies and approaches to take Tradeshift to the next level. 

Job Description

Role
As a Machine Learning Engineer on the ML team you will develop machine learning powered features to the Tradeshift B2B platform. You will work with product managers to define how the product should behave, develop predictive models for the core implementation and work on serving the model and integrated it as part as a large distributed system. You will also help other product teams to incorporate machine learning into their products.

What a day is like:
You will design and implement server systems that serve machine learning models and the surrounding business logic to integrate with other software components. You will also develop the machine learning models themselves, using data that you find in our databases and Spark-based data lake. You will write production-grade, peer-reviewed code with automated tests and keep an eye on the production operation of your team’s services.  You will collaborate with product managers, designers, and the frontend engineers on the team to deliver the best user experience.

Qualifications

  • Master’s degree in Computer Science, Statistics, Mathematics, Physics or similar.
  • Have 2+ years of professional experience with machine learning products.
  • Strong programming skills. You create high quality, maintainable, testable code that solves real world problems. Preferably, you know Java, Python or C++ and its associated machine learning and web development frameworks
  • Experience with Machine Learning, statistical inference or similar. Building software products based on predictive models is your game. 
  • You have knowledge of machine learning techniques such as SVMs, logistic regression, deep neural networks, cross validation, naive bayes, feature extraction, avoiding overfitting, structured prediction, etc
  • Experience with data processing infrastructure such as Spark, Hadoop, SQL, Elasticsearch and Amazon Web Services is a plus.
  • Experience in an area of applied machine learning, such as Document Classification, Information Extraction, Fraud Detection is a plus.
  • You are creative, intelligent, independent and take responsibility.
  • You understand how your technical solutions contribute to realizing a broader vision, and you have a passion for interacting with many different people to achieve a goal.
  • We are looking for a colleague that can challenge us, define new solutions and see them through to implementation
  • You are fluent in English speaking, reading and writing
     

You also have:

  • Experience with Deep Learning and associated frameworks is a plus.
  • Working experience in structured development and build environments (continuous integration, automated testing, automated configuration and deployment)Experience in cloud-based development and associated tools is a plus.

Additional Information

Location
Our office in Copenhagen has a palpable excitement that stems from the constant change that keeps everyone on their toes. Each employee has a voice, and their hard work pays off. No good work goes unnoticed. 

Culture 
Our culture began day one when three Danes poured their brains, heart, and guts into creating a platform that could connect every business in the world. We expect each employee to approach their work with the same amount of pride and passion. One day you might find us having a ping pong match in the middle of the work day, and then you’ll find us handing off projects to colleagues in different time zones so we can continue progress around the clock. 

TradeShifters come from various backgrounds and nations, and we all thrive off challenging the status quo. We take pride in nurturing employee happiness, encouraging personal development, and welcoming teammates from all walks of life.

We value diversity and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Why you might like working here:

  • You love autonomy and the freedom to get your work done how you want 
  • You like sharing your opinions and feeling like they matter
  • You want to work for a company that requires you to bring your whole self to work every day: brains, heart, and guts.
  • Ambitious international startup
  • Career and professional development opportunities
  • Large office that provides caters to many different work-environment preferences  
  • Flexible work hours
  • Mobile phone plan and at home internet
  • Lunch and snacks daily with drinks
  • A competitive compensation package and equity
  • In-house activities like yoga
  • Opportunity to join many fun, varied company events like happy hours, hackathons, family holiday parties, and many more.
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